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Optimal updating magnitude in adaptive flat-distribution sampling.
Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery.
Afiliação
  • Zhang C; Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch, Galveston, Texas 77555-0304, USA.
  • Drake JA; Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch, Galveston, Texas 77555-0304, USA.
  • Ma J; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.
  • Pettitt BM; Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch, Galveston, Texas 77555-0304, USA.
J Chem Phys ; 147(17): 174105, 2017 Nov 07.
Article em En | MEDLINE | ID: mdl-29117700
We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Chem Phys Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Chem Phys Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos